Recent evidence indicates a link between gut pathology and microbiome with hypertension (HTN) in animal models. However, whether this association exists in humans is unknown. Thus, our objectives in the present study were to test the hypotheses that high blood pressure (BP) patients have distinct gut microbiomes and that gut-epithelial barrier function markers and microbiome composition could predict systolic BP (SBP). Fecal samples, analyzed by shotgun metagenomics, displayed taxonomic and functional changes, including altered butyrate production between patients with high BP and reference subjects. Significant increases in plasma of intestinal fatty acid binding protein (I-FABP), lipopolysaccharide (LPS), and augmented gut-targetting proinflammatory T helper 17 (Th17) cells in high BP patients demonstrated increased intestinal inflammation and permeability. Zonulin, a gut epithelial tight junction protein regulator, was markedly elevated, further supporting gut barrier dysfunction in high BP. Zonulin strongly correlated with SBP (R2 = 0.5301, P<0.0001). Two models predicting SBP were built using stepwise linear regression analysis of microbiome data and circulating markers of gut health, and validated in a separate cohort by prediction of SBP from zonulin in plasma (R2 = 0.4608, P<0.0001). The mouse model of HTN, chronic angiotensin II (Ang II) infusion, was used to confirm the effects of butyrate and gut barrier function on the cardiovascular system and BP. These results support our conclusion that intestinal barrier dysfunction and microbiome function are linked to HTN in humans. They suggest that manipulation of gut microbiome and its barrier functions could be the new therapeutic and diagnostic avenues for HTN.

Imbalance of gut microbiome and intestinal epithelial barrier dysfunction in patients with high blood pressure.

https://researchportal.port.ac.uk/portal/files/15176804/METTL1_Promotes_let_7.pdf

METTL1 Promotes let-7 MicroRNA Processing via m7G Methylation

Human-targeted drugs may exert off-target effects or can be repurposed to modulate the gut microbiota. However, our understanding of such effects is limited due to a lack of rapid and scalable assay to comprehensively assess microbiome responses to drugs. Drugs and other compounds can drastically change the overall abundance, taxonomic composition, and functions of a gut microbiome. Here, we developed an approach to screen compounds against individual microbiomes in vitro, using metaproteomics to both measure absolute bacterial abundances and to functionally profile the microbiome. Our approach was evaluated by testing 43 compounds (including 4 antibiotics) against 5 individual microbiomes. The method generated technically highly reproducible readouts, including changes of overall microbiome abundance, microbiome composition, and functional pathways. Results show that besides the antibiotics, the compounds berberine and ibuprofen inhibited the accumulation of biomass during in vitro growth of the microbiota. By comparing genus and species level-biomass contributions, selective antibacterial-like activities were found with 35 of the 39 non-antibiotic compounds. Seven of the compounds led to a global alteration of the metaproteome, with apparent compound-specific patterns of functional responses. The taxonomic distributions of altered proteins varied among drugs, i.e., different drugs affect functions of different members of the microbiome. We also showed that bacterial function can shift in response to drugs without a change in the abundance of the bacteria. Current drug-microbiome interaction studies largely focus on relative microbiome composition and microbial drug metabolism. In contrast, our workflow enables multiple insights into microbiome absolute abundance and functional responses to drugs. The workflow is robust, reproducible, and quantitative and is scalable for personalized high-throughput drug screening applications.

/pdf/rapidaim-a-culture-and-metaproteomics-based-rapid-assay-of-wj21mhbh1i.pdf

RapidAIM: a culture- and metaproteomics-based Rapid Assay of Individual Microbiome responses to drugs

European Union Seventh Framework Programme [FP7/2007-2013] under the grant agreement [306000-STATegra]; Marie Curie International Research Staff Exchange Scheme under grant agreement [612583-DEANN]; Spanish MINECO [BIO2012-40244]. INB Grant [PT17/0009/0015 - ISCIII-SGEFI / ERDF]. Funding for open access charge: MINECO [BIO2012-40244].

PaintOmics 3: a web resource for the pathway analysis and visualization of multi-omics data.

Pulmonary arterial hypertension (PAH) is considered a disease of the pulmonary vasculature. Limited progress has been made in preventing or arresting progression of PAH despite extensive efforts. O...

https://www.ahajournals.org/doi/pdf/10.1161/HYPERTENSIONAHA.119.14294

Altered Gut Microbiome Profile in Patients With Pulmonary Arterial Hypertension.

Pathway analysis is widely used in omics studies. Pathway-based data integration and visualization is a critical component of the analysis. To address this need, we recently developed a novel R package called Pathview. Pathview maps, integrates and renders a large variety of biological data onto molecular pathway graphs. Here we developed the Pathview Web server, as to make pathway visualization and data integration accessible to all scientists, including those without the special computing skills or resources. Pathview Web features an intuitive graphical web interface and a user centered design. The server not only expands the core functions of Pathview, but also provides many useful features not available in the offline R package. Importantly, the server presents a comprehensive workflow for both regular and integrated pathway analysis of multiple omics data. In addition, the server also provides a RESTful API for programmatic access and conveniently integration in third-party software or workflows. Pathview Web is openly and freely accessible at https://pathview.uncc.edu/.

/pdf/pathview-web-user-friendly-pathway-visualization-and-data-3jzh01kyu1.pdf

Yeshvant K. Bhavnasi

Papers

Pathview Web: user friendly pathway visualization and data integration.